Data Science Analyst

Broad Street, Greater London
3 months ago
Applications closed

Related Jobs

View all jobs

Junior Data Analyst

Data Scientist

Data Architect

Head of Data, Pricing and Commercial Analytics

Junior / Graduate Data Scientist

Insight & Intelligence Manager (18 Months FTC)

Our client, a well-established and actively expanding Lloyd's Syndicate Insurance firm, is seeking a Data Science Analyst with a strong interest in AI / ML and other emerging data & automation related technology to join an expanding team in an expanding business that regard Data Science and the utilisation of Artificial Intelligence & Machine Learning as the core driver of their continued success.

The ideal candidate will have proven data modelling experience, be familiar with Data Science concepts/techniques and a desire to further their knowledge of AI and LLM’s (Large Language Models) You will be joining a small team that own their processes end-to-end and are encouraged to adopt a “Test > Learn > Improve” method to ensure continuous improvement through the utilisation of AI & Machine Learning.

From a technology perspective you will be comfortable with manipulating SQL based data and have programming experience with statistical based languages (e.g.) Python or R.

THE ROLE:

  • You will be responsible for assisting the development of data processes and models to support operations across various business functions including Pricing, Underwriting and Claims.

  • You will assist in developing data models and generating valuable insights to support the management of schemes and brokers across various products, while also contributing to pricing development and the pricing cycle.

  • You will utilise your knowledge of data modelling and data science techniques, applying them as needed to meet specific project requirements.

    RESPONSIBILITIES:

  • Utilise analytical, data science and AI approaches to assist with the development of models, and generation of data insight to support various business functions.

  • Support end-to-end implementation & continuous improvement of analytical processes through development, testing and deployment

  • Continuously develop skills through on-the-job learning, industry events, online courses, and other external learning opportunities.

  • Work with management to align activities with the company’s strategy and broader business goals.

  • Stay updated on the latest trends in data science and AI/ML methodologies both within and beyond the Insurance sector.

  • Effective communicator, able to explain and present technical concepts to others.

  • Strong interpersonal skills to build and maintain value adding relationships with different business functions

    SKILLS / EXPERIENCE REQUIRED:

  • Proficient in data manipulation and statistical tools such as Python, R, and SQL Server.

  • Experience working with a range of data types, including structured and unstructured data utilising appropriate Data Science techniques.

  • Is able to demonstrate a keen interest and knowledge/awareness of emerging data technology (e.g.) AI, LLM’s, Machine Learning, Deep Learning; and demonstrates the to apply emerging theory to practical situations

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How Many Robotics Tools Do You Need to Know to Get a Robotics Job?

If you’re pursuing a career in robotics, it can feel like the list of tools you should learn never ends. One job advert asks for ROS, another mentions Gazebo, another wants experience with Python, Linux, C++, RobotStudio, MATLAB/Simulink, perception stacks, control frameworks, real-time OS, vision libraries — and that’s just scratching the surface. With so many frameworks, languages and platforms, it’s no wonder robotics job seekers feel overwhelmed. But here’s the honest truth most recruiters won’t say explicitly: 👉 They don’t hire you because you know every tool — they hire you because you can apply the right tools to solve real robotics problems reliably and explain your reasoning clearly. Tools matter — but only in service of outcomes. So the real question isn’t how many tools you should know, but which tools you should master and why. For most robotics roles, the answer is significantly fewer — and far more focused — than you might assume. This article breaks down what employers really expect, which tools are core, which are role-specific, and how to focus your learning so you look capable, confident, and ready to contribute from day one.

What Hiring Managers Look for First in Robotics Job Applications (UK Guide)

Robotics is one of the most dynamic, interdisciplinary fields in technology — blending mechanical systems, embedded software, controls, perception (AI/vision), modelling, simulation and systems integration. Hiring managers in this space are highly selective because robotics teams need people who can solve real-world problems under constraints, work across disciplines, and deliver safe, reliable systems. And here’s the reality: hiring managers do not read every word of your CV. Like in many tech domains, they scan quickly — often forming a judgement in the first 10–20 seconds. In robotics, those first signals are especially important because the work is complex and there’s a wide range of candidate backgrounds. This guide unpacks exactly what hiring managers look for first in robotics applications and how to optimise your CV, portfolio and cover letter so you stand out in the UK market.

The Skills Gap in Robotics Jobs: What Universities Aren’t Teaching

Robotics is no longer confined to science fiction or isolated research labs. Today, robots perform critical tasks across manufacturing, healthcare, logistics, agriculture, defence, hospitality and even education. In the UK, businesses are embracing automation to improve productivity, reduce costs and tackle labour shortages. Yet despite strong interest and a growing number of university programmes in robotics, many employers report a persistent problem: graduates are not job-ready for real-world robotics roles. This is not a question of intelligence or dedication. It is a widening skills gap between what universities teach and what employers actually need in robotics jobs. In this article, we’ll explore that gap in depth — what universities do well, where their programmes often fall short, why the disconnect exists, what employers really want, and how you can bridge the divide to build a thriving career in robotics.